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An Improved Squirrel Search Algorithm for Global Function Optimization

Direct Superbubble Detection

by 1,2,* and 1,2,3,4,5,6,7
Competence Center for Scalable Data Services and Solutions Dresden/Leipzig, Universität Leipzig, Augustusplatz 12, D-04107 Leipzig, Germany
Bioinformatics Group, Department of Computer Science, Universität Leipzig, Härtelstraße 16–18, D-04107 Leipzig, Germany
Interdisciplinary Center for Bioinformatics, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, and Leipzig Research Center for Civilization Diseases, University Leipzig, D-04107 Leipzig, Germany
Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany
Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Wien, Austria
Facultad de Ciencias, Universidad National de Colombia, Sede Bogotá, Colombia
Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
Author to whom correspondence should be addressed.
Algorithms 2019, 12(4), 81;
Received: 7 March 2019 / Revised: 10 April 2019 / Accepted: 12 April 2019 / Published: 17 April 2019
Superbubbles are a class of induced subgraphs in digraphs that play an essential role in assembly algorithms for high-throughput sequencing data. They are connected with the remainder of the host digraph by a single entrance and a single exit vertex. Linear-time algorithms for the enumeration superbubbles recently have become available. Current approaches require the decomposition of the input digraph into strongly-connected components, which are then analyzed separately. In principle, a single depth-first search could be used, provided one can guarantee that the root of the depth-first search (DFS)-tree is not itself located in the interior or the exit point of a superbubble. Here, we describe a linear-time algorithm to determine suitable roots for a DFS-forest that is guaranteed to identify the superbubbles in a digraph correctly. In addition to the advantages of a more straightforward implementation, we observe a nearly three-fold gain in performance on real-world datasets. We present a reference implementation of the new algorithm that accepts many commonly-used input formats for digraphs. It is available as open source from github. View Full-Text
Keywords: superbubble; depth-first search; cycles; linear time algorithm superbubble; depth-first search; cycles; linear time algorithm
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MDPI and ACS Style

Gärtner, F.; Stadler, P.F. Direct Superbubble Detection. Algorithms 2019, 12, 81.

AMA Style

Gärtner F, Stadler PF. Direct Superbubble Detection. Algorithms. 2019; 12(4):81.

Chicago/Turabian Style

Gärtner, Fabian, and Peter F. Stadler. 2019. "Direct Superbubble Detection" Algorithms 12, no. 4: 81.

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